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ORCIDThomas Martinetz
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- affiliation: University of Lübeck, Germany
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2020 – today
- 2024
[c87]Kathleen Anderson, Thomas Martinetz:
Revealing Unintentional Information Leakage in Low-Dimensional Facial Portrait Representations. ICANN (1) 2024: 163-177- [c86]Christoph Linse
, Beatrice Brückner, Thomas Martinetz:
Enhancing Generalization in Convolutional Neural Networks Through Regularization with Edge and Line Features. ICANN (1) 2024: 432-446 - [c85]Christoph Linse, Erhardt Barth, Thomas Martinetz:
Leaky ReLUs That Differ in Forward and Backward Pass Facilitate Activation Maximization in Deep Neural Networks. IJCNN 2024: 1-8 - [c84]Julius Martinetz, Christoph Linse, Thomas Martinetz:
Rethinking generalization of classifiers in separable classes scenarios and over-parameterized regimes. IJCNN 2024: 1-10 - 2023
- [c83]Marius Jahrens, Hans-Oliver Hansen, Rebecca Köhler, Thomas Martinetz:
Population Coding Can Greatly Improve Performance of Neural Networks: A Comparison. ICANN (5) 2023: 386-398 - [c82]Christoph Linse, Thomas Martinetz:
Large Neural Networks Learning from Scratch with Very Few Data and without Explicit Regularization. ICMLC 2023: 279-283 - [c81]Christoph Linse, Erhardt Barth, Thomas Martinetz:
Convolutional Neural Networks Do Work with Pre-Defined Filters. IJCNN 2023: 1-8 - 2022
- [j40]Christoph Linse, Hammam A. Alshazly, Thomas Martinetz:
A walk in the black-box: 3D visualization of large neural networks in virtual reality. Neural Comput. Appl. 34(23): 21237-21252 (2022) - [i11]Christoph Linse, Thomas Martinetz:
Large Neural Networks Learning from Scratch with Very Few Data and without Regularization. CoRR abs/2205.08836 (2022) - [i10]Julius Martinetz, Thomas Martinetz:
Highly over-parameterized classifiers generalize since bad solutions are rare. CoRR abs/2211.03570 (2022) - 2021
- [j39]Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Sahar Ahmed Idris, Thomas Martinetz:
Towards Explainable Ear Recognition Systems Using Deep Residual Networks. IEEE Access 9: 122254-122273 (2021) - [j38]Shambhavi Mishra, Tanveer Ahmed, Vipul Kumar Mishra, Manjit Kaur, Thomas Martinetz, Amit Kumar Jain, Hammam A. Alshazly:
Multivariate and Online Prediction of Closing Price Using Kernel Adaptive Filtering. Comput. Intell. Neurosci. 2021: 6400045:1-6400045:14 (2021) - [j37]Hammam A. Alshazly, Christoph Linse, Mohamed Abdalla, Erhardt Barth, Thomas Martinetz:
COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans. PeerJ Comput. Sci. 7: e655 (2021) - [j36]Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz:
Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning. Sensors 21(2): 455 (2021) - [c80]Dominik Mairhöfer, Manuel Laufer, Paul Martin Simon, Malte Sieren, Arpad Bischof, Thomas Käster, Erhardt Barth, Jörg Barkhausen, Thomas Martinetz:
An AI-based Framework for Diagnostic Quality Assessment of Ankle Radiographs. MIDL 2021: 484-496 - 2020
- [j35]Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz:
Deep Convolutional Neural Networks for Unconstrained Ear Recognition. IEEE Access 8: 170295-170310 (2020) - [c79]Philipp Grüning, Thomas Martinetz, Erhardt Barth:
Log-Nets: Logarithmic Feature-Product Layers Yield More Compact Networks. ICANN (2) 2020: 79-91 - [c78]Marius Jahrens, Thomas Martinetz:
Solving Raven's Progressive Matrices with Multi-Layer Relation Networks. IJCNN 2020: 1-6 - [i9]Marius Jahrens, Thomas Martinetz:
Solving Raven's Progressive Matrices with Multi-Layer Relation Networks. CoRR abs/2003.11608 (2020) - [i8]Philipp Grüning, Thomas Martinetz, Erhardt Barth:
Feature Products Yield Efficient Networks. CoRR abs/2008.07930 (2020) - [i7]Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz:
Explainable COVID-19 Detection Using Chest CT Scans and Deep Learning. CoRR abs/2011.05317 (2020)
2010 – 2019
- 2019
- [j34]Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz:
Ensembles of Deep Learning Models and Transfer Learning for Ear Recognition. Sensors 19(19): 4139 (2019) - [j33]Hammam A. Alshazly, Christoph Linse, Erhardt Barth, Thomas Martinetz:
Handcrafted versus CNN Features for Ear Recognition. Symmetry 11(12): 1493 (2019) - [c77]Marius Jahrens, Thomas Martinetz:
Multi-layer relation networks for relational reasoning. APPIS 2019: 10:1-10:5 - 2018
- [i6]Marius Jahrens, Thomas Martinetz:
Multi-layer Relation Networks. CoRR abs/1811.01838 (2018) - 2017
- [c76]Irina Burciu, Thomas Martinetz, Erhardt Barth:
Sensing Forest for Pattern Recognition. ACIVS 2017: 126-137 - [c75]Amir Madany Mamlouk, Martin Haker, Thomas Martinetz:
Perception space analysis: From color vision to odor perception. IJCNN 2017: 689-696 - [c74]Boris Knyazev, Erhardt Barth, Thomas Martinetz:
Recursive autoconvolution for unsupervised learning of convolutional neural networks. IJCNN 2017: 2486-2493 - [i5]Lars Hertel, Erhardt Barth, Thomas Käster, Thomas Martinetz:
Deep Convolutional Neural Networks as Generic Feature Extractors. CoRR abs/1710.02286 (2017) - 2016
- [j32]Michael Schellenberger Costa, Jan Born, Jens Christian Claussen, Thomas Martinetz:
Modeling the effect of sleep regulation on a neural mass model. J. Comput. Neurosci. 41(1): 15-28 (2016) - [j31]Michael Schellenberger Costa, Arne Weigenand, Hong-Viet Victor Ngo, Lisa Marshall, Jan Born, Thomas Martinetz, Jens Christian Claussen:
A Thalamocortical Neural Mass Model of the EEG during NREM Sleep and Its Response to Auditory Stimulation. PLoS Comput. Biol. 12(9) (2016) - [j30]Henry Schütze, Erhardt Barth, Thomas Martinetz:
Learning Efficient Data Representations With Orthogonal Sparse Coding. IEEE Trans. Computational Imaging 2(3): 177-189 (2016) - [c73]Irina Burciu, Thomas Martinetz, Erhardt Barth:
Hierarchical Manifold Sensing with Foveation and Adaptive Partitioning of the Dataset. HVEI 2016: 1-10 - [i4]Boris Knyazev, Erhardt Barth, Thomas Martinetz:
Autoconvolution for Unsupervised Feature Learning. CoRR abs/1606.00611 (2016) - 2015
- [j29]Foti Coleca, Andreea State, Sascha Klement, Erhardt Barth, Thomas Martinetz:
Self-organizing maps for hand and full body tracking. Neurocomputing 147: 174-184 (2015) - [j28]Jens Hocke, Thomas Martinetz:
Maximum distance minimization for feature weighting. Pattern Recognit. Lett. 52: 48-52 (2015) - [c72]Irina Burciu, Thomas Martinetz, Erhardt Barth:
Foveated Manifold Sensing for object recognition. BlackSeaCom 2015: 196-200 - [c71]Lars Hertel, Erhardt Barth, Thomas Käster, Thomas Martinetz:
Deep convolutional neural networks as generic feature extractors. IJCNN 2015: 1-4 - [c70]Henry Schütze, Erhardt Barth, Thomas Martinetz:
Learning orthogonal sparse representations by using geodesic flow optimization. IJCNN 2015: 1-8 - 2014
- [j27]Arne Weigenand, Michael Schellenberger Costa, Hong-Viet Victor Ngo, Jens Christian Claussen, Thomas Martinetz:
Characterization of K-Complexes and Slow Wave Activity in a Neural Mass Model. PLoS Comput. Biol. 10(11) (2014) - [c69]Barbara Hammer, Haibo He, Thomas Martinetz:
Learning and modeling big data. ESANN 2014 - [c68]Henry Schütze, Erhardt Barth, Thomas Martinetz:
An adaptive hierarchical sensing scheme for sparse signals. Human Vision and Electronic Imaging 2014: 90140G - [c67]Irina Burciu, Adrian Ion-Margineanu, Thomas Martinetz, Erhardt Barth:
Visual manifold sensing. Human Vision and Electronic Imaging 2014: 90141B - [c66]Jens Hocke, Thomas Martinetz:
Global Metric Learning by Gradient Descent. ICANN 2014: 129-135 - [c65]Foti Coleca, Sabrina Zîrnovean, Thomas Käster, Thomas Martinetz, Erhardt Barth:
Key-point Detection with Multi-layer Center-surround Inhibition. VISAPP (1) 2014: 386-393 - [i3]Bogdan Miclut, Thomas Käster, Thomas Martinetz, Erhardt Barth:
Committees of deep feedforward networks trained with few data. CoRR abs/1406.5947 (2014) - 2013
- [j26]Sascha Klement, Silke Anders, Thomas Martinetz:
The Support Feature Machine: Classification with the Least Number of Features and Application to Neuroimaging Data. Neural Comput. 25(6): 1548-1584 (2013) - [c64]Foti Coleca, Thomas Martinetz, Erhardt Barth:
Gesture Interfaces with Depth Sensors. Time-of-Flight and Depth Imaging 2013: 207-227 - [c63]Foti Coleca, Sascha Klement, Thomas Martinetz, Erhardt Barth:
Real-time skeleton tracking for embedded systems. Multimedia Content and Mobile Devices 2013: 86671X - [c62]Mike Wellner, Thomas Käster, Thomas Martinetz, Erhardt Barth:
Optimizing depth-of-field based on a range map and a wavelet transform. Multimedia Content and Mobile Devices 2013: 86671U - [c61]Jens Hocke, Thomas Martinetz:
Feature Weighting by Maximum Distance Minimization. ICANN 2013: 420-425 - 2012
- [j25]Thomas Binder, Thomas Martinetz:
On the boundedness of an Iteration involving Points on the Hypersphere. Int. J. Comput. Geom. Appl. 22(6): 499-516 (2012) - [j24]Jens Hocke, Kai Labusch, Erhardt Barth, Thomas Martinetz:
Sparse Coding and Selected Applications. Künstliche Intell. 26(4): 349-355 (2012) - [j23]Eleonora Vig, Michael Dorr, Thomas Martinetz, Erhardt Barth:
Intrinsic Dimensionality Predicts the Saliency of Natural Dynamic Scenes. IEEE Trans. Pattern Anal. Mach. Intell. 34(6): 1080-1091 (2012) - [c60]Jens Hocke, Erhardt Barth, Thomas Martinetz:
Application of non-linear transform coding to image processing. Human Vision and Electronic Imaging 2012: 829105 - [c59]Thomas Binder, Florian Kriener, Christian Wichner, Manuel Wille, Mike Wellner, Thomas Käster, Thomas Martinetz, Erhardt Barth:
How to make a small phone camera shoot like a big DSLR: creating and fusing multi-modal exposure series. Human Vision and Electronic Imaging 2012: 829106 - [c58]Henry Schütze, Thomas Martinetz, Silke Anders, Amir Madany Mamlouk:
A Multivariate Approach to Estimate Complexity of FMRI Time Series. ICANN (2) 2012: 540-547 - [c57]Horia Coman, Erhardt Barth, Thomas Martinetz:
Sparse Coding Neural Gas Applied to Image Recognition. WSOM 2012: 105-114 - [c56]Andreea State, Foti Coleca, Erhardt Barth, Thomas Martinetz:
Hand Tracking with an Extended Self-Organizing Map. WSOM 2012: 115-124 - 2011
- [j22]Jiajie Zhang, Amir Madany Mamlouk, Thomas Martinetz, Suhua Chang, Jing Wang, Rolf Hilgenfeld:
PhyloMap: an algorithm for visualizing relationships of large sequence data sets and its application to the influenza A virus genome. BMC Bioinform. 12: 248 (2011) - [j21]Krishna Kumar Kandaswamy, Ganesan Pugalenthi, Mehrnaz Khodam Hazrati, Kai-Uwe Kalies, Thomas Martinetz:
BLProt: Prediction of bioluminescent proteins based on Support Vector Machine and ReliefF feature selection. BMC Bioinform. 12: 345 (2011) - [j20]Eleonora Vig, Michael Dorr, Thomas Martinetz, Erhardt Barth:
Eye Movements Show Optimal Average Anticipation with Natural Dynamic Scenes. Cogn. Comput. 3(1): 79-88 (2011) - [j19]John Aldo Lee, Frank-Michael Schleif, Thomas Martinetz:
Advances in artificial neural networks, machine learning, and computational intelligence. Neurocomputing 74(9): 1299-1300 (2011) - [j18]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Soft-competitive learning of sparse codes and its application to image reconstruction. Neurocomputing 74(9): 1418-1428 (2011) - [j17]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Robust and Fast Learning of Sparse Codes With Stochastic Gradient Descent. IEEE J. Sel. Top. Signal Process. 5(5): 1048-1060 (2011) - [c55]Sascha Klement, Thomas Martinetz:
On the Problem of Finding the Least Number of Features by L1-Norm Minimisation. ICANN (1) 2011: 315-322 - 2010
- [j16]Martin Böhme, Martin Haker, Thomas Martinetz, Erhardt Barth:
Shading constraint improves accuracy of time-of-flight measurements. Comput. Vis. Image Underst. 114(12): 1329-1335 (2010) - [c54]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Bag of Pursuits and Neural Gas for Improved Sparse Coding. COMPSTAT 2010: 327-336 - [c53]Kai Labusch, Thomas Martinetz:
Learning sparse codes for image reconstruction. ESANN 2010 - [c52]Eleonora Vig, Michael Dorr, Thomas Martinetz, Erhardt Barth:
A Learned Saliency Predictor for Dynamic Natural Scenes. ICANN (3) 2010: 52-61 - [c51]Sascha Klement, Thomas Martinetz:
The Support Feature Machine for Classifying with the Least Number of Features. ICANN (2) 2010: 88-93 - [c50]Sascha Klement, Thomas Martinetz:
A New Approach to Classification with the Least Number of Features. ICMLA 2010: 141-146 - [c49]Fabian Timm, Thomas Martinetz:
Statistical Fourier Descriptors for Defect Image Classification. ICPR 2010: 4190-4193 - [i2]Thomas Binder, Thomas Martinetz:
On the boundedness of an iteration involving points on the hypersphere. CoRR abs/1001.1624 (2010)
2000 – 2009
- 2009
- [j15]Dirk Repsilber, Thomas Martinetz, Mats Björklund:
Adaptive Dynamics of Regulatory Networks: Size Matters. EURASIP J. Bioinform. Syst. Biol. 2009 (2009) - [j14]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Sparse Coding Neural Gas: Learning of overcomplete data representations. Neurocomputing 72(7-9): 1547-1555 (2009) - [j13]Thomas Martinetz, Kai Labusch, Daniel Schneegaß:
SoftDoubleMaxMinOver: Perceptron-Like Training of Support Vector Machines. IEEE Trans. Neural Networks 20(7): 1061-1072 (2009) - [c48]Martin Haker, Martin Böhme, Thomas Martinetz, Erhardt Barth:
Self-Organizing Maps for Pose Estimation with a Time-of-Flight Camera. Dyn3D 2009: 142-153 - [c47]Martin Böhme, Martin Haker, Kolja Riemer, Thomas Martinetz, Erhardt Barth:
Face Detection Using a Time-of-Flight Camera. Dyn3D 2009: 167-176 - [c46]Martin Haker, Martin Böhme, Thomas Martinetz, Erhardt Barth:
Deictic Gestures with a Time-of-Flight Camera. Gesture Workshop 2009: 110-121 - [c45]Martin Haker, Thomas Martinetz, Erhardt Barth:
Multimodal Sparse Features for Object Detection. ICANN (2) 2009: 923-932 - [c44]Fabian Timm, Sascha Klement, Thomas Martinetz, Erhardt Barth:
Welding Inspection using Novel Specularity Features and a One-class SVM. VISAPP (1) 2009: 146-153 - [c43]Fabian Timm, Thomas Martinetz, Erhardt Barth:
Optical Inspection of Welding Seams. VISIGRAPP (Selected Papers) 2009: 269-282 - [c42]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Approaching the Time Dependent Cocktail Party Problem with Online Sparse Coding Neural Gas. WSOM 2009: 145-153 - 2008
- [j12]Martin Böhme, Martin Haker, Thomas Martinetz, Erhardt Barth:
A facial feature tracker for human-computer interaction based on 3D Time-Of-Flight cameras. Int. J. Intell. Syst. Technol. Appl. 5(3/4): 264-273 (2008) - [j11]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Simple Method for High-Performance Digit Recognition Based on Sparse Coding. IEEE Trans. Neural Networks 19(11): 1985-1989 (2008) - [c41]Martin Böhme, Martin Haker, Thomas Martinetz, Erhardt Barth:
Shading constraint improves accuracy of time-of-flight measurements. CVPR Workshops 2008: 1-6 - [c40]Martin Haker, Martin Böhme, Thomas Martinetz, Erhardt Barth:
Scale-invariant range features for time-of-flight camera applications. CVPR Workshops 2008: 1-6 - [c39]Kai Labusch, Fabian Timm, Thomas Martinetz:
Simple Incremental One-Class Support Vector Classification. DAGM-Symposium 2008: 21-30 - [c38]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Learning Data Representations with Sparse Coding Neural Gas. ESANN 2008: 233-238 - [c37]Martin Böhme, Michael Dorr, Mathis Graw, Thomas Martinetz, Erhardt Barth:
A software framework for simulating eye trackers. ETRA 2008: 251-258 - [c36]Sascha Klement, Amir Madany Mamlouk, Thomas Martinetz:
Reliability of Cross-Validation for SVMs in High-Dimensional, Low Sample Size Scenarios. ICANN (1) 2008: 41-50 - [c35]Kai Labusch, Erhardt Barth, Thomas Martinetz:
Sparse Coding Neural Gas for the Separation of Noisy Overcomplete Sources. ICANN (1) 2008: 788-797 - [c34]Fabian Timm, Sascha Klement, Thomas Martinetz:
Fast model selection for MaxMinOver-based training of support vector machines. ICPR 2008: 1-4 - [c33]Daniel Schneegaß, Steffen Udluft, Thomas Martinetz:
Uncertainty propagation for quality assurance in Reinforcement Learning. IJCNN 2008: 2588-2595 - 2007
- [c32]Daniel Schneegaß, Steffen Udluft, Thomas Martinetz:
Neural Rewards Regression for near-optimal policy identification in Markovian and partial observable environments. ESANN 2007: 301-306 - [c31]Daniel Schneegaß, Anton Maximilian Schäfer, Thomas Martinetz:
The Intrinsic Recurrent Support Vector Machine. ESANN 2007: 325-330 - [c30]Daniel Schneegaß, Steffen Udluft, Thomas Martinetz:
Explicit Kernel Rewards Regression for data-efficient near-optimal policy identification. ESANN 2007: 337-342 - [c29]Kai Labusch, Udo Siewert, Thomas Martinetz, Erhardt Barth:
Learning optimal features for visual pattern recognition. Human Vision and Electronic Imaging 2007: 64920B - [c28]Daniel Schneegaß, Steffen Udluft, Thomas Martinetz:
Improving Optimality of Neural Rewards Regression for Data-Efficient Batch Near-Optimal Policy Identification. ICANN (1) 2007: 109-118 - 2006
- [j10]Martin Böhme, Michael Dorr, Christopher Krause, Thomas Martinetz, Erhardt Barth:
Eye movement predictions on natural videos. Neurocomputing 69(16-18): 1996-2004 (2006) - [c27]Daniel Schneegaß, Steffen Udluft, Thomas Martinetz:
Kernel Rewards Regression: An Information Efficient Batch Policy Iteration Approach. Artificial Intelligence and Applications 2006: 428-433 - [c26]Daniel Schneegaß, Thomas Martinetz, Michael Clausohm:
OnlineDoubleMaxMinOver: a simple approximate time and information efficient online Support Vector Classification method. ESANN 2006: 575-580 - [c25]Martin Böhme, Michael Dorr, Thomas Martinetz, Erhardt Barth:
Gaze-contingent temporal filtering of video. ETRA 2006: 109-115 - [c24]Erhardt Barth, Michael Dorr, Martin Böhme, Karl R. Gegenfurtner, Thomas Martinetz:
Guiding the mind's eye: improving communication and vision by external control of the scanpath. Human Vision and Electronic Imaging 2006: 60570D - [c23]Daniel Schneegaß, Kai Labusch, Thomas Martinetz:
MaxMinOver Regression: A Simple Incremental Approach for Support Vector Function Approximation. ICANN (1) 2006: 150-158 - [c22]Erhardt Barth, Michael Dorr, Martin Böhme, Karl R. Gegenfurtner, Thomas Martinetz:
Guiding Eye Movements for Better Communication and Augmented Vision. PIT 2006: 1-8 - [c21]Michael Dorr, Martin Böhme, Thomas Martinetz, Erhardt Barth:
Gaze-Contingent Spatio-temporal Filtering in a Head-Mounted Display. PIT 2006: 205-207 - [c20]André Meyer, Martin Böhme, Thomas Martinetz, Erhardt Barth:
A Single-Camera Remote Eye Tracker. PIT 2006: 208-211 - [c19]Thomas Martinetz, Amir Madany Mamlouk, Cicero Mota:
Fast and Easy Computation of Approximate Smallest Enclosing Balls. SIBGRAPI 2006: 163-170 - 2005
- [j9]Anke Meyer-Bäse, Karsten Jancke, Axel Wismüller, Simon Foo, Thomas Martinetz:
Medical image compression using topology-preserving neural networks. Eng. Appl. Artif. Intell. 18(4): 383-392 (2005) - [j8]Amir Madany Mamlouk, Hannah Sharp, Kerstin M. L. Menne, Ulrich G. Hofmann, Thomas Martinetz:
Unsupervised spike sorting with ICA and its evaluation using GENESIS simulations. Neurocomputing 65-66: 275-282 (2005) - [c18]Michael Dorr, Thomas Martinetz, Martin Böhme, Erhardt Barth:
Visibility of temporal blur on a gaze-contingent display. APGV 2005: 33-36 - [c17]Thomas Martinetz, Kai Labusch, Daniel Schneegaß:
SoftDoubleMinOver: A Simple Procedure for Maximum Margin Classification. ICANN (2) 2005: 301-306 - [e1]Uwe Brinkschulte, Jürgen Becker, Dietmar Fey, Christian Hochberger, Thomas Martinetz, Christian Müller-Schloer, Hartmut Schmeck, Theo Ungerer, Rolf P. Würtz:
18th International Conference on Architecture of Computing Systems, Workshops, Innsbruck, Austria, March 2005. VDE Verlag 2005, ISBN 3-8007-2880-X [contents] - 2004
- [j7]Amir Madany Mamlouk, Thomas Martinetz:
On the dimensions of the olfactory perception space. Neurocomputing 58-60: 1019-1025 (2004) - [j6]Jan T. Kim, Jan E. Gewehr, Thomas Martinetz:
Binding Matrix: a Novel Approach for Binding Site Recognition. J. Bioinform. Comput. Biol. 2(2): 289-308 (2004) - [c16]Thomas Martinetz:
MinOver Revisited for Incremental Support-Vector-Classification. DAGM-Symposium 2004: 187-194 - [c15]Martin Böhme, Christopher Krause, Thomas Martinetz, Erhardt Barth:
Saliency Extraction for Gaze-Contingent Displays. GI Jahrestagung (2) 2004: 646-650 - 2003
- [c14]Amir Madany Mamlouk, Jan T. Kim, Erhardt Barth, Michael Brauckmann, Thomas Martinetz:
One-Class Classification with Subgaussians. DAGM-Symposium 2003: 346-353 - [c13]Anke Meyer-Bäse, Thomas D. Otto, Thomas Martinetz, Dorothee Auer, Axel Wismüller:
Model-Free Functional MRI Analysis Using Topographic Independent Component Analysis. ESANN 2003: 509-514 - [c12]Erhardt Barth, Jan Drewes, Thomas Martinetz:
Individual predictions of eye-movements with dynamic scenes. Human Vision and Electronic Imaging 2003: 252-259 - [c11]Erhardt Barth, Jan Drewes, Thomas Martinetz:
Dynamic predictions of tracked gaze. ISSPA (1) 2003: 245-248 - 2001
- [c10]Daniel Polani, Thomas Martinetz, Jan T. Kim:
An Information-Theoretic Approach for the Quantification of Relevance. ECAL 2001: 704-713 - [c9]Jan T. Kim, Thomas Martinetz, Daniel Polani:
On the Effects of Transcription Factor Properties on the Information Content of Binding Sites. German Conference on Bioinformatics 2001: 192-194 - [c8]Martin Haker, André Meyer, Daniel Polani, Thomas Martinetz:
A Method for Incorporation of New Evidence to Improve World State Estimation. RoboCup 2001: 362-367 - 2000
- [c7]Daniel Polani, Thomas Martinetz:
Team Description for Lucky Lübeck - Evidence-Based World State Estimation. RoboCup 2000: 481-484
1990 – 1999
- 1999
- [c6]Claus O. Wilke, Christopher Ronnewinkel, Thomas Martinetz:
Molecular Evolution in Time-Dependent Environments. ECAL 1999: 417-421 - [i1]Christopher Ronnewinkel, Claus O. Wilke, Thomas Martinetz:
Genetic Algorithms in Time-Dependent Environments. CoRR physics/9911006 (1999) - 1997
- [j5]Thomas Villmann, Ralf Der, J. Michael Herrmann, Thomas Martinetz:
Topology preservation in self-organizing feature maps: exact definition and measurement. IEEE Trans. Neural Networks 8(2): 256-266 (1997) - 1995
- [c5]Thomas Martinetz, Peter Protzel, Otto Gramckow, Günter Sörgel:
Neural Network Control for Steel Rolling Mills. SNN Symposium on Neural Networks 1995: 280-286 - 1994
- [j4]Thomas Martinetz, Klaus Schulten:
Topology representing networks. Neural Networks 7(3): 507-522 (1994) - [c4]Thomas Villmann, Ralf Der, J. Michael Herrmann, Thomas Martinetz:
Topology Preservation in Self-Organizing Feature Maps: General Definition and Efficient Measurement. Fuzzy Days 1994: 159-166 - 1993
- [j3]Thomas Martinetz, Stanislav G. Berkovich, Klaus Schulten:
'Neural-gas' network for vector quantization and its application to time-series prediction. IEEE Trans. Neural Networks 4(4): 558-569 (1993) - [c3]Thomas Martinetz, Klaus Schulten:
A neural network with Hebbian-like adaptation rules learning visuomotor coordination of a PUMA robot. ICNN 1993: 820-822 - 1992
- [b3]Helge J. Ritter, Thomas Martinetz, Klaus Schulten:
Neural computation and self-organizing maps - an introduction. Computation and neural systems series, Addison-Wesley 1992, ISBN 978-0-201-55443-4, pp. 1-306 - [b2]Thomas Martinetz:
Selbstorganisierende neuronale Netzwerkmodelle zur Bewegungssteuerung. Technical University Munich, Germany, DISKI 14, Infix Verlag, St. Augustin, Germany 1992, ISBN 3-929037-14-9, pp. 1-167 - 1991
- [b1]Helge J. Ritter, Thomas Martinetz, Klaus Schulten:
Neuronale Netze - eine Einführung in die Neuroinformatik selbstorganisierter Netzwerke (2. Aufl.). Reihe Künstliche Intelligenz, Addison-Wesley 1991, ISBN 978-3-89319-131-4, pp. 1-325 - [c2]Stan Berkovitch, Philippe Dalger, Ted Hesselroth, Thomas Martinetz, Benoît Noël, Jörg A. Walter, Klaus Schulten:
Vector Quantization Algorithm for Time Series Prediction and Visuo-Motor Control of Robots. Wissensbasierte Systeme 1991: 443-447 - 1990
- [j2]Thomas Martinetz, Helge J. Ritter, Klaus Schulten:
Three-dimensional neural net for learning visuomotor coordination of a robot arm. IEEE Trans. Neural Networks 1(1): 131-136 (1990) - [c1]Thomas Martinetz, Klaus Schulten:
Hierarchical neural net for learning control of a robot's arm and gripper. IJCNN 1990: 747-752
1980 – 1989
- 1989
- [j1]Helge J. Ritter, Thomas Martinetz, Klaus Schulten:
Topology-conserving maps for learning visuo-motor-coordination. Neural Networks 2(3): 159-168 (1989)
Coauthor Index
[c85] [c81] [j39] [j37] [j36] [c80] [j35] [c79] [i8] [i7] [j34] [j33] [c76] [c74] [i5] [j30] [c73] [i4] [j29] [c72] [c71] [c70] [c68] [c67] [c65] [i3] [c64] [c63] [c62] [j24] [j23] [c60] [c59] [c57] [c56] [j20] [j18] [j17] [j16] [c54] [c52] [j14] [c48] [c47] [c46] [c45] [c44] [c43] [c42] [j12] [j11] [c41] [c40] [c38] [c37] [c35] [c29] [j10] [c25] [c24] [c22] [c21] [c20] [c18] [c15] [c14] [c12] [c11]
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Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-10-07 22:06 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
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dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
